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Me, Myself, and AI

Me, Myself, and AI
Author: MIT Sloan Management Review and Boston Consulting Group (BCG)
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Why do only 10% of companies succeed with AI? In this series by MIT SMR and BCG, we talk to the leaders who've achieved big wins with AI in their companies and learn how they did it. Hear what gets experts from companies like Microsoft, Delta Air Lines, and others excited to do their jobs every day and what they consider the keys to their success.
60 Episodes
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At Amnesty Tech, a division of human rights organization Amnesty International, Damini Satija and Matt Mahmoudi leverage their expertise in technology and public policy to examine the use of AI in the public sector and its impact on citizens worldwide.
In Part 1 of Matt and Damini’s conversation with Sam and Shervin, they described scenarios in which AI tools can put human rights at risk and how their work is helping to expose those risks and protect people from the technology’s misuse. In this episode, they resume their conversation and dig deeper into the ways AI regulations can limit the negative use of AI at scale. Matt and Damini also caution us about what a dystopian future might hold and point to specific ways leaders in the corporate world can help limit the harms of AI. Read this episode's transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bios:
Matt Mahmoudi is a lecturer, researcher, and organizer. He’s been leading Amnesty International’s research and advocacy efforts on banning facial recognition technologies and exposing their uses against racialized communities, from New York City to the occupied Palestinian territories. He was the inaugural recipient of the Jo Cox Ph.D. scholarship at the University of Cambridge, where he studied digital urban infrastructures as new frontiers for racial capitalism and remains an affiliated lecturer in sociology. His work has appeared in the journals The Sociological Review and International Political Sociology and the book Digital Witness (Oxford University Press, 2020). His forthcoming book is Migrants in the Digital Periphery: New Urban Frontiers of Control (University of California Press, 2023).
Damini Satija is a human rights and public policy expert working on data and artificial intelligence, with a focus on algorithmic discrimination, welfare automation, government surveillance, and tech equity. She is head of the Algorithmic Accountability Lab and a deputy director at Amnesty Tech. She previously worked as an adviser to the U.K. government on data and AI ethics and represented the U.K. as a policy expert on AI and human rights at the Council of Europe. She has a master’s degree in public administration from Columbia University’s School of International and Public Affairs.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
Amnesty International brings together more than 10 million staff members and volunteers worldwide to advocate for social justice. Damini Satija and Matt Mahmoudi work with Amnesty Tech, a division of the human rights organization that focuses on the role of government, Big Tech, and technologies like artificial intelligence in areas like surveillance, discrimination, and bias.
On this episode, Matt and Damini join Sam and Shervin to highlight scenarios in which AI tools can put human rights at risk, such as when governments and public-sector agencies use facial recognition systems to track social activists or algorithms to make automated decisions about public housing access and child welfare. Damini and Matt caution that AI technology cannot fix human problems like bias, discrimination, and inequality; that will take human intervention and changes to public policy. Read the episode transcript here.
For more on what organizations can do to combat the unintended negative consequences arising from the use of automated technologies, tune in to our next episode, Part 2 of our conversation with Matt and Damini, airing September 13, 2023.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bios:
Matt Mahmoudi is a lecturer, researcher, and organizer. He’s been leading Amnesty International’s research and advocacy efforts on banning facial recognition technologies and exposing their uses against racialized communities, from New York City to the occupied Palestinian territories. He was the inaugural recipient of the Jo Cox Ph.D. scholarship at the University of Cambridge, where he studied digital urban infrastructures as new frontiers for racial capitalism and remains an affiliated lecturer in sociology. His work has appeared in the journals The Sociological Review and International Political Sociology and the book Digital Witness (Oxford University Press, 2020). His forthcoming book is Migrants in the Digital Periphery: New Urban Frontiers of Control (University of California Press, 2023).
Damini Satija is a human rights and public policy expert working on data and artificial intelligence, with a focus on algorithmic discrimination, welfare automation, government surveillance, and tech equity. She is head of the Algorithmic Accountability Lab and a deputy director at Amnesty Tech. She previously worked as an adviser to the U.K. government on data and AI ethics and represented the U.K. as a policy expert on AI and human rights at the Council of Europe. She has a master’s degree in public administration from Columbia University’s School of International and Public Affairs.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
Jeremy King leads a team of 1,400 passionate engineers working on the continuous improvement of Pinterest’s image-driven platform. With a background that includes heading up a translation team at eBay and overseeing the technology behind Walmart’s U.S. retail stores and e-commerce business, Jeremy is now responsible for technology operations at Pinterest. To support the company’s mission to inspire people to “create a life that they love,” he and his team rely on advanced AI, machine learning, and a graph database to index and build a network of images so users can find inspiration — particularly when they aren’t completely sure what they’re looking for.
On this episode, Jeremy joins Sam and Shervin to talk about some recent advances Pinterest has made in the image-recognition space and shares his views on how generative AI will transform image-based content like Pinterest’s. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Jeremy King is senior vice president of technology at Pinterest, where he leads the company’s technical vision and the engineering organization responsible for building and scaling a visual discovery engine.
Before joining Pinterest, he was CTO and senior vice president at Walmart, where he led the team responsible for the technology behind U.S. retail stores and e-commerce for Walmart and Jet, and oversaw customer, merchant, and supply chain technologies across cloud and data platforms. King has also held executive-level technology roles at Walmart Labs, LiveOps, and eBay.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
When Zan Gilani came to the U.S. from Pakistan to complete his undergraduate studies, he chose to study Chinese because it was rumored to be a difficult language. At the time, the tech industry was booming, and he quickly became interested in applying his passion for foreign languages and learning more generally in a technology-rich environment.
Those interests led Zan to Duolingo, where he has been working in product management for eight years and now oversees the app company’s experiential AI team. What excites him about working at the language-learning app company is his ability to help build solutions that enable personalized education at scale: The app boasts over 16 million daily active users, and AI-driven functionality motivates them through frequent notifications, personalizes learning experiences by adjusting the difficulty of questions in practice sessions, and observes and critiques learners’ performance.
Zan joins our podcast to outline the specific ways Duolingo uses AI and machine learning to drive user engagement, and discuss how the technology can be used to support learning more generally. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Zan Gilani is a principal product manager at Duolingo. For the past eight years, he has helped grow the company’s learner base from 3 million to 16 million daily active users by working on retention, acquisition, growth in Asia, gamification, and the new-user experience.
He currently leads Duolingo’s Experimental AI team, which uses generative AI to build features that teach learners more effectively. More broadly, Gilani is working on setting Duolingo up for success using generative AI, through external partnerships and internal education.
Gilani grew up in Karachi, Pakistan, and is currently based in New York City. He has bachelor’s degrees in political science and East Asian studies from Columbia University.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
Naba Banerjee’s identity as a “forever learner” led to her become the first female engineer in her family. That curiosity has informed her career choices as well, leading her to companies as varied as Tata, Cognizent, Walmart, and AAA. Now, as director of trust product and operations at vacation rental platform Airbnb, she is continuing let her curiosity be her guide as she applies her previous data science experience to the travel industry. On this episode, Naba joins Shervin and Sam to talk abouthow she and her team use AI and machine learning to increase the safety of the guests and hosts who use Airbnb’s platform. She also discusses collaboration between humans and machines and the importance of recognizing that neither is an infallible decision maker. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Naba Banerjee is the director of trust product and operations at Airbnb, overseeing the company’s efforts to combat fraud, build trust between hosts and guests, and stop bad actors from using the platform. Her most recent work includes the development of Airbnb’s reservation screening technology, which helps to identify users making potentially high-risk reservations and prevent them from taking advantage of the platform. Banerjee has over two decades of experience building products that deliver innovative, customer-centric solutions. She joined Airbnb after spending 13 years at Walmart.com, where she played an instrumental role in the evolution of product management, including shipping packages to customers more quickly and building mobile apps to enable customers to check out faster.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
As CEO of Aboitiz Data Innovation, David Hardoon oversees the operations of a technology conglomerate focused on using data science and AI to support its businesses in a range of sectors, including banking, financial services, utilities, agriculture, and construction in Singapore and the Philippines. In his role, David is leading some unexpected — but practical — uses of artificial intelligence, including using voice and image recognition to detect stress in livestock, and analyzing internet-of-things data to reduce waste and CO2 emissions in the cement R&D process.
David joins this episode to discuss the broad scope of the organizations he’s responsible for, the role of AI regulation and governance in helping to spur innovation, humans’ sometimes problematic role in shaping AI outputs, and how a high school detention led to a career in artificial intelligence. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
David Hardoon is the CEO of Aboitiz Data Innovation and chief data and AI officer of Union Bank of the Philippines. He is concurrently the chief data and innovation officer of the Aboitiz Group and chief data officer of UnionDigital Bank. Previously, he was the Monetary Authority of Singapore’s first appointed chief data officer and head of the Data Analytics Group, as well as a special adviser on AI. Hardoon has a doctorate in computer science (machine learning) from the University of Southampton and a bachelor’s degree from Royal Holloway, University of London, in computer science and AI.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
When Elizabeth Anne Watkins started her doctoral program, she landed a research role studying journalists’ use of security and privacy technologies — but she found the security tools confusing and difficult to use. Today, as a research scientist in the social science of AI at Intel Labs, she advocates for other end users faced with understanding and working with new technologies.
Elizabeth employs social science to understand the concerns of technicians performing complex chip manufacturing processes so that new AI systems will be developed to better serve those human experts. During this process, she also helps the technicians recognize AI’s role as a supporting technology — even a coworker — rather than a human replacement.
She joins this episode to discuss her role as a social scientist working in tech and some of the ways Intel is applying AI technologies like computer vision and natural language processing to improve semiconductor manufacturing processes. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Elizabeth Anne Watkins is a research scientist in the Social Science of Artificial Intelligence at Intel Labs and a member of Intel’s Responsible AI Advisory Council, where she applies social science methods to amplify human potential in human-AI collaboration. Her research on the design, deployment, and governance of AI tools has been published in leading academic journals and has been featured in Wired, MIT Technology Review, and Harvard Business Review. She was previously a postdoctoral fellow at Princeton and has a doctorate from Columbia University and a master’s degree from MI
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
Hina Dixit’s interest in supporting people and solving problems has its roots in her family’s call office business, where she helped people place telephone calls when she was growing up in India. Later, after earning her bachelor’s degree in computer science, she was quickly recruited into the tech space, where her problem-solving and customer service skills have served her well as both a software engineer and tech investor. From a developer role at Symantec, to project leader at Apple, to an AI investor role at Samsung Next, Hina continues to leverage her communication and connection skills in seeking out and supporting innovations in artificial intelligence, as well as robotics, Web3, and other tech sectors.
On this episode, Hina shares the criteria she considers when making investments in new entrepreneurial ventures. She also highlights the focus areas that are of most interest right now, explains why she enjoys mentoring other technologists, and shares her views on what the future of AI looks like. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Naba Banerjee is the director of trust product and operations at Airbnb, overseeing the company’s efforts to combat fraud, build trust between hosts and guests, and stop bad actors from using the platform. Her most recent work includes the development of Airbnb’s reservation screening technology, which helps to identify users making potentially high-risk reservations and prevent them from taking advantage of the platform. Banerjee has over two decades of experience building products that deliver innovative, customer-centric solutions. She joined Airbnb after spending 13 years at Walmart.com, where she played an instrumental role in the evolution of product management, including shipping packages to customers more quickly and building mobile apps to enable customers to check out faster.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
Shelia Anderson parlayed a love of learning into studying the emerging field of engineering when she began her undergraduate education. After gaining experience leading IT teams in the technology, airline, and insurance industries, she joined Aflac in the summer of 2022.
Shelia joins Sam and Shervin to share how using artificial intelligence and machine learning to automate the processing of somewhat routine insurance claims frees up staff members to spend more time serving customers and processing more complex, higher-value claims. She also discusses the types of skills she looks for in data science and engineering talent beyond technical capabilities, and why she believes the insurance industry offers a great opportunity for people interested in a career working with AI and machine learning. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
*NEW! For specific takeaways from this episode and guidance on how you can implement them in your own work, download our episode toolkit here.
Guest bio:
Shelia Anderson joined Aflac in July 2022 as senior vice president and CIO. She is responsible for overseeing the company’s digital services division and driving technology strategy in support of the insurer’s U.S. business. Anderson has a rich history as an executive leading the IT functions at Fortune 500 global organizations, including Liberty Mutual, USAA, HP, and Electronic Data Systems.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
Stephanie Moyerman’s background in cosmology and astrophysics — where she worked with large data sets, looking for a signal among what was mostly noise — prepared her well for a career in data science and ethics. Today, she is the data science director of well-being at Instagram, where she works to enhance trust, safety, and integrity for users of the social media platform.
Stephanie joins Sam and Shervin on this episode to discuss how applying artificial intelligence to social media enables Instagram to detect fraud and abuse at scale to help protect users, as well as the importance of human input in AI feedback loops and the need for more experienced practitioners in the field. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
*NEW! For specific takeaways from this episode and guidance on how you can implement them in your own work, download our episode toolkit here.
Guest bio:
Stephanie Moyerman is the data science director of well-being at Instagram, where she works to minimize negative experiences and maximize positive experiences on the platform. Previously, she was the senior director of risk and trust science at eBay and a senior science manager in Amazon’s Customer Trust and Partner Support unit, where she worked to protect the e-commerce platforms from bad actors.
Moyerman has a doctorate in physics (experimental cosmology) and a master’s in computational science, math, and engineering from the University of California, San Diego. She also has dual bachelor’s degrees in mathematics and physics from Harvey Mudd College.
Moyerman enjoys many hobbies, including running, hiking, surfing, snowboarding, judo, jujitsu, glassblowing, flying airplanes, and racing cars.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
Wildlife conservation efforts may not be the first thing that comes to mind when one thinks about opportunities to use artificial intelligence and machine learning. But Dave Thau, data and technology lead scientist at the World Wildlife Fund (WWF), can share myriad examples of how these technologies are helping our planet.
On this episode, Dave joins Sam and Shervin to discuss WWF’s many uses of AI and machine learning. Among them are applications that predict deforestation, analyze images from motion-sensitive cameras to identify species, optimize wildlife patrols to catch poachers, and reduce the illegal wildlife trade online. These conservation efforts are not only supported by nonprofit partners with shared goals but by tech-company partners that are sharing advanced AI technologies. Read the episode transcript here.
NEW! For specific takeaways from this episode and guidance on how you can implement them in your own work, download our episode toolkit here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Dave Thau is the World Wildlife Fund’s data and technology global lead scientist, focusing on applying artificial intelligence in conservation and using technology for long-term impact monitoring.
Previously, he worked at Google, where he helped launch Google Earth Engine and managed developer relations. He also helped to develop the Global Forest Watch nature monitoring platform with the World Resources Institute, and the Map of Life species data platform.
Thau’s work in data management, sustainability, AI, and remote sensing has been published in several journals. He is also a member of the Knowledge and Data Task Force for the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.
Thau has a doctorate in computer science from the University of California, Davis.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
Rathi Murthy has always been passionate about technology roles that allow her to drive business transformation and improve customer experience. In her current role as CTO and president of Product & Technology for Expedia Group, she’s able to do both. One of her key goals is to enhance and unify the end-user experience across Expedia’s many brands, among them Hotels.com, Vrbo, and Travelocity. Another transformation goal: helping to modernize the entire travel industry by making Expedia’s AI technology available to B2B partners throughout the travel ecosystem, such as hotels, airlines, car rental companies, and cruise lines.
Expedia Group’s travel platform processes more than 600 billion AI predictions each year and relies on AI and machine learning technology to provide a range of services, including fraud prevention, customer service through virtual agents, flight price comparisons, and quick and seamless travel booking. Rathi joins Sam and Shervin to explain how Expedia Group is using artificial intelligence to continually improve the customer experience for travelers and travel providers alike. Read the episode transcript here.
New! For specific takeaways from this episode and guidance on how you can implement them in your own work, download our episode toolkit here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Rathi Murthy is CTO and president of Expedia Product & Technology. In this role, she focuses on accelerating Expedia Group’s Open World platform, developing accessible and equitable products, and delivering quality experiences for travelers, partners, and developers.
Previously, as CTO, she oversaw Verizon Media’s global technology strategy, including its platform technology and infrastructure and innovations in 5G. As CTO at Gap Inc., she developed an end-to-end technology strategy for its portfolio of brands. She has also held senior technology leadership roles at American Express, eBay, Yahoo, Sun Microsystems, and WebMD.
Murthy currently sits on the board of directors for PagerDuty. She has a master’s degree in computer engineering from Santa Clara University.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
Anders Butzbach Christensen began his career in product management before landing his dream job working for the Lego Group in Denmark. Today, as head of data engineering, he’s leading Lego’s digital transformation with a specific focus on designing and building data products, including self-service applications that technology and business teams can all use to better serve their customers.
In this episode, Anders joins Sam and Shervin to describe how the Lego Group is approaching digital transformation, and how the toymaker is empowering its product teams by becoming a product-, architecture-, and engineering-led company. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
As head of data engineering at the Lego Group, Anders Butzbach Christensen is responsible for building up a strong competency area and great data products that will enable the company to become more data-driven. The product teams he leads are currently building a self-service core data platform to ensure that employees can discover and use data across the organization.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
Michelle McCrackin, senior manager of analytics learning and development at Delta Air Lines, never imagined that she’d be an analytics leader when she first joined the airline as an HR business partner. But, faced with the challenge of hiring outside analytics talent, she proposed a solution that would change her career path along with the paths of other Delta employees: an internal analytics training program. Delta Analytics Academy (DAA) enables front-line employees to gain in-demand tech skills and the opportunity to advance within the organization. In December 2022, DAA graduated its first cohort of 12 students, selected from a pool of 750 applicants that included gate agents, baggage handlers, flight attendants, and other operational experts interested in learning how data and analytics can be applied to process-improvement challenges.
In this episode, Michelle joins Sam and Shervin to discuss how the program, started in partnership with Georgia State University, fits into the airline’s talent development and retention strategy. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Michelle McCrackin is a strategy and analytics leader with over 13 years of experience in the corporate space. She worked in the consumer packaged goods and automotive industries before moving into the field of aviation, where she is currently senior manager of analytics, learning, and development at Delta Air Lines. McCrackin’s passion for raising the analytics capability across the operations and commercial functions at Delta is exhibited in creation and development of Delta Analytics Academy (DAA), a program with the objective of producing an internal talent pipeline and closing the talent gap within the analytics skill set. DAA was developed in partnership with Georgia State University based on the hypothesis that taking an industry expert and providing them with a wraparound analytics education in a condensed format would produce top-performing analytics professionals.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
As a partner with OpenAI — the company that recently wowed the tech world and the general public with its DALL-E image generator and ChatGPT chatbot — Microsoft helped to make those generative AI tools possible. But Microsoft has long invested in developing its own artificial intelligence technologies, for internal and external customers alike. And even when AI is not the centerpiece of a specific software program, it’s often driving how that tool — such as the company’s Bing search engine — works.
As corporate vice president of Microsoft’s AI platform, Eric Boyd oversees product and technology teams that build artificial intelligence and machine solutions for the company’s Azure platform and its AI services portfolio. Eric joins Sam and Shervin on this episode to talk about how Microsoft builds AI tools and embeds the technology in its various products, AI’s potential for helping to expand people’s creativity, and the democratization of AI. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Eric Boyd leads the AI platform team within Microsoft’s Cloud + AI division. This global organization includes Azure Machine Learning, Microsoft Cognitive Services, Azure Cognitive Search, and internal platforms that provide data, experimentation, and graphics processing units cluster management to groups across Microsoft.
Boyd joined the company in 2009 to create the Silicon Valley Search Ads team. In 2011, he moved to Bellevue, Washington, to lead the Bing Ads Development team before taking on his current role in 2015.
Before joining Microsoft, Boyd was the vice president of engineering at Mochi Media, an ads startup that was acquired by Shanda Games. Previously, he was vice president of platform engineering at Yahoo for 10 years.
Boyd has a bachelor’s degree in computer science from MIT.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
When Ziad Obermeyer was a resident in an emergency medicine program, he found himself lying awake at night worrying about the complex elements of patient diagnoses that physicians could miss. He subsequently found his way to data science and research and has since coauthored numerous papers on algorithmic bias and the use of AI and machine learning in predictive analytics in health care.
Ziad joins Sam and Shervin to talk about his career trajectory and highlight some of the potentially breakthrough research he has conducted that’s aimed at preventing death from cardiac events, preventing Alzheimer’s disease, and treating other acute and chronic conditions. Read the episode transcript here.
For more about Ziad: http://ziadobermeyer.com/research
Nightingale Open Science: https://www.nightingalescience.org/
Dandelion Health: https://dandelionhealth.ai/
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Dr. Ziad Obermeyer works at the intersection of machine learning and health. He is an associate professor and the Blue Cross of California Distinguished Professor at the University of California, Berkeley; a Chan Zuckerberg Biohub Investigator; and a faculty research fellow at the National Bureau of Economic Research. His papers have appeared in a wide range of journals, including Science, Nature Medicine, and The New England Journal of Medicine; his work on algorithmic bias is frequently cited in the public debate about artificial intelligence. He is a cofounder of Nightingale Open Science, a nonprofit that makes massive new medical imaging data sets available for research, and Dandelion, a platform for AI innovation in health. Obermeyer continues to practice emergency medicine in underserved communities.
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While Me, Myself, and AI is on winter break, we hope you enjoy this bonus episode excerpted from an MIT Sloan Management Review-BCG webinar based on our 2020 research report, "Expanding AI's Impact With Organizational Learning."
Download a PDF copy of the slide deck from this webinar here.
Follow along with our speakers:
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Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
With a background in building enterprise platforms for organizations, including Oracle and Walmart, Wayfair CTO Fiona Tan oversees all of the technology initiatives for the Boston-based e-commerce company. As the home furnishings retailer begins to open brick-and-mortar stores, it’s taking lessons learned from the digital space to inform how it markets its home products to customers in physical locations.
On this episode, Fiona joins Sam and Shervin to discuss how artificial intelligence fuels nearly everything the retailer does, from ad purchasing to product pricing, and where human decision makers fit in. She also describes how AI enables Wayfair’s marketing automation technology, as well as some innovative new programs underway to help customers experience the company’s products virtually. Read the episode transcript here.
Read the 2022 MIT Sloan Management Review-BCG Artificial Intelligence and Business Strategy report here: sloanreview.mit.edu/ai2022.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Fiona Tan is the chief technology officer at Wayfair, where she oversees a global innovation team responsible for creating market-leading experiences through the home furnishings retailer’s world-class e-commerce platform. Before joining Wayfair, Tan served as senior vice president of U.S. technology at Walmart, where she was responsible for innovation and engineering execution spanning its site, mobile app, and all associate and merchant-facing technology across its e-commerce business and retail stores in the United States.
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We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
Khatereh (KK) Khodavirdi is focused on using AI to create better customer experiences — a process she compares to creating an “AI Legoland,” in which various technology components fit together to build cohesive solutions for PayPal’s customers. This is an approach she is applying in her role as senior director of data science in the online payment systems company’s consumer products division, where she oversees data science teams for PayPal, its peer-to-peer payment app Venmo, and e-commerce coupon-finder Honey.
On this episode, KK joins Sam and Shervin to describe how PayPal’s various consumer products work together to help users have a seamless experience across its products. She also talks about AI’s role in further personalizing the customer experience across the company’s brand portfolio, data governance challenges following corporate acquisitions, and her approach to creating effective teams. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
In her role as senior director of data science, Khatereh Khodavirdi leads a cross-functional team of data scientists, analytics experts, and strategists to help accelerate revenue growth through data and insights for PayPal, Venmo, and Honey. She was a founding member of eBay’s advertising data team and has spent her career building analytics functions to accelerate growth initiatives in commerce, advertising, monetization, and digital payments, with increasing levels of responsibility.
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We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
Ameen Kazerouni, chief data and analytics officer at Orangetheory Fitness (OTF), believes that AI’s role isn’t to replace human experts but rather to help them make better decisions. That’s why OTF collects heart rate and telemetry data during its in-studio fitness classes: so that AI algorithms can turn that data into feedback that empowers people to make real-time choices about their workouts and enables coaches to offer personalized recommendations.
On this episode, Ameen joins Sam and Shervin to describe how OTF’s data collection and algorithms are used to create a curated fitness experience for its members, and he explains why it’s critical to keep humans in the feedback loop when implementing artificial intelligence. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Ameen Kazerouni is chief data and analytics officer at Orangetheory Fitness. Over the course of his career, Kazerouni has had the opportunity to use machine learning in a variety of fields, including clinical research, medical imaging, data warehouse design, e-commerce, and now health and wellness. He is currently focused on the challenges of operationalizing large volumes of data into scalable customer solutions and strategic initiatives.
A core belief of his is to “build experiences, not algorithms,” which drives his team to put forward scalable solutions with measurable impact on real-world use cases. In his free time, Kazerouni enjoys keeping up to date with the latest methods in artificial intelligence and the newest comedy specials on Netflix, burning his savings on expanding his smart home, and marching down the path of becoming bionic by quantifying himself with any and all wearable fitness tech.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.
I would love to look at that data. humans are so weird sometimes